COVID-19 has caused most corporate businesses that remain open to shift to a work from home, remote workplace. Because of this, the cybersecurity industry has been turned on its head. Security teams went from monitoring and protecting established network environments to quickly pivoting their tools, resources, and oversight to manage a distributed workforce. This has created an extremely volatile network security environment unlike any we have seen before.                                                                                                                                                                                  

According to Google, “Every day, Gmail blocks more than 100 million phishing emails. During the last week, we saw 18 million daily malware and phishing emails related to COVID-19. This is in addition to more than 240 million COVID-related daily spam messages.”

Other popular malicious acts that have come of age in this pandemic environment:

  • Remote User Credential Theft: This one affects the work from home policy most directly as it has to do with attackers taking the opportunity of a mass amount of remote connections happening to easily conceal malicious logins without being detected by their target’s security team.
  • Phishing Emails with Malware: Phishing emails are one of the most prevalent threats when working from home because working off a personal computer can be significantly less safe than one and the office that has the organizations cybersecurity software.
  • Malicious Websites: Websites with Coronavirus or COVID-19 in the url or title are being reported as malicious left and right. Everyone should be wary of taking any advice from these sites or clicking on any links as they too may have malware.
  • Zero-Day-Attacks: Although the threat of a Zero-Day-Attack is always looming, and companies should be prepared regardless, with COVID-19 demanding the focus of security professionals on remote logins, hackers have no better time than the present to launch an obliterative attack to steal companies’ data.

So, how do enterprises and organizations deal with this? Right now there are two options: 

  1. Hire more security professionals to watch over the network 24/7 while your already established security team works on securing the user credentials and login processes.
  2. Adopt an AI system to catch possible threats on the network so your security team can focus their attention where it is needed. 

The first option is almost impossible to execute in the current industry climate. There is a massive lack of employable cybersecurity professionals right now. Even before the outbreak of the current global pandemic, enterprises were hurting in the cybersecurity hiring department.  

Companies are struggling to find employable security professionals to handle an ever increasing and evolving number of new threats from bad actors and an overabundance of security alerts from the systems used to support them.

Not to mention most companies are tightening their budgets due to the pandemic and cannot spend more money to hire employees. 

The second is the one thing all cybersecurity teas should have during Covid-19.

AI-Powered Network Traffic Analysis

In the face of professional and budgetary shortfalls, an AI solution capable of detecting anomalous behavior on a network is an ideal solution. However, it’s important for enterprises to understand exactly what kind of AI they will be getting when deciding on a NTA platform. 

Many security providers claim to have intelligent AI capabilities, but often their technology still leans on a labeling-model that requires hours upon hours of human-led training time to label threats. 

What enterprises need is an AI system capable of distinguishing what is a threat and what isn’t – all on its own. That’s called Self-Supervised AI and is based on a machine learning all on it’s own instead of having humans label each instance of a breach or threat. 

The AI that we are using at MixMode is in the class of generative models in Self-Supervised Learning, that basically gives it this predictive ability. It collects data to form a baseline of the network and will be able to predict what will happen over time because of its knowledge of what a day of the week looks like for the network. 

If anything strays from this baseline, the platform will alert whichever security team oversees it that there has been an irregularity detected in network performance that should be adhering to the baseline standard – all without human intervention.

Instead of spending days, weeks, and even months labeling potential threats and sifting through mountains of false positives, enterprise security teams can install the MixMode Platform and watch as it learns the ins and outs of their network in only 7 days

Because of its predictive power, the Self-Supervised learning model is capable of preventing Zero-Day attacks, which makes it the best security method out there and has the fastest response time to any breach.

Hackers are upping their game with adversarial AI and new attack methods every single day. Is your team meeting the challenge?

Learn more about Network Traffic Analysis with MixMode’s self-learning AI here. 

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